基于新鲜度和配送成本的易腐食品配送路径
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摘要
为解决企业在制定易腐食品配送计划时难以权衡配送总成本与交付产品的新鲜度的问题,建立以配送总成本最低和交付产品平均新鲜度最大为目标,带时间窗的易腐食品配送路径规划模型。采用自适应差分进化(differential evolution,DE)算法求解模型,通过数值算例验证模型和算法的有效性。与基本DE算法和基本蚁群算法的求解结果进行对比,自适应DE算法的求解结果更优,收敛速度更快。求得的帕累托解集表明配送总成本与交付产品平均新鲜度相悖,增加少量的配送成本可以使交付产品的平均新鲜度得到大幅提升。对易腐食品保质期、时间窗宽度和车辆装载量进行灵敏度分析,为企业在不同配送情景下在配送总成本与交付产品的平均新鲜度之间的权衡提供参考。
In order to solve the problem enterprises faced with when making the highly perishable food distribution planning that it is difficult to balance between the total cost of distribution and the freshness of delivery products,a distribution route planning model of perishable food with time window is established with the objectives of the minimum total cost of distribution and the maximum average freshness of products. The adaptive differential evolution( DE) algorithm is used to solve the model. A numerical example is used to verify the validity of the model and the algorithm. Compared with the results of the basic DE algorithm and the basic ant colony algorithm,the adaptive DE algorithm has better results and faster convergence speed. The obtained Pareto solution set shows that the relationship between the total cost of delivery and the average freshness of delivery products are contrary. By increasing a small amount of distribution cost,the average freshness of delivery products can be greatly improved. Sensitivity analysis onperishable food shelf-life,time window width and vehicle loading provides reference for enterprises to balance between the total cost of delivery and the average freshness of delivered products under different distribution scenarios.
In order to solve the problem enterprises faced with when making the highly perishable food distribution planning that it is difficult to balance between the total cost of distribution and the freshness of delivery products,a distribution route planning model of perishable food with time window is established with the objectives of the minimum total cost of distribution and the maximum average freshness of products. The adaptive differential evolution( DE) algorithm is used to solve the model. A numerical example is used to verify the validity of the model and the algorithm. Compared with the results of the basic DE algorithm and the basic ant colony algorithm,the adaptive DE algorithm has better results and faster convergence speed. The obtained Pareto solution set shows that the relationship between the total cost of delivery and the average freshness of delivery products are contrary. By increasing a small amount of distribution cost,the average freshness of delivery products can be greatly improved. Sensitivity analysis onperishable food shelf-life,time window width and vehicle loading provides reference for enterprises to balance between the total cost of delivery and the average freshness of delivered products under different distribution scenarios.
引文
[1]吴瑶,马祖军.时变路网下带时间窗的易腐食品生产–配送问题[J].系统工程理论与实践,2017,37(1):172-181.DOI:10.12011/1000-6788(2017)01-0172-10.
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[7]邵举平,曹倩,沈敏燕,等.生鲜农产品配送中带时间窗的VRP模型与算法[J].工业工程与管理,2015(1):122-127.
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[9]杨晓芳,姚宇,付强.基于新鲜度的冷链物流配送多目标优化模型[J].计算机应用研究,2016,33(4):1050-1053.DOI:10.3969./j.issn.1001-3695.2016.04.019.
[10]吴忠和,陈宏,赵千,等.时间约束下鲜活农产品供应链应急协调契约[J].系统管理学报,2014,23(1):49-56.
[11] BARKAOUI M,BERGER J,BOUKHTOUTA A.Customer satisfaction in dynamic vehicle routing problem with time windows[J].Applied Soft Computing,2015,35:423-432.DOI:10.1016/j.asoc.2015.06.035.
[12] SCHYNS M.An ant colony system for responsive dynamic vehicle routing[J].European Journal of Operational Research,2015,245(3):704-718.DOI:10.1016/j.ejor.2015.04.009.
[13]陈玉光,陈志祥.基于准时送货和最小耗油的配送车辆路径问题研究[J].中国管理科学,2015,23(s1):156-164.
[14]周辉仁,唐万生,王海龙.基于差分进化算法的多旅行商问题优化[J].系统工程理论与实践,2010,30(8):1471-1476.
[15] ZHANG Jingqiao,SANDERSON A C.JADE:adaptive differential evolution with optional external archive[J].IEEE Transactions on Evolutionary Computation,2009,13(5):945-958.
[2] SHUKLA M,JHARKHARIA S.Artificial immune system-based algorithm for vehicle routing problem with time window constraint for the delivery of agri-fresh produce[J].Journal of Decision Systems,2013,22(3):224-247.DOI:10.1080/12460125.2013.810859.
[3] AMORIM P,PARRAGH S N,SPERANDIO F,et al.A rich vehicle routing problem dealing with perishable food:a case study[J].TOP,2014,22(2):489-508.DOI:10.1007/s11750-012-0266-4.
[4] CHEN H K,HSUEH C F,CHANG M S.Production scheduling and vehicle routing with time windows for perishable food products[J].Computers&Operations Research,2009,36(7):2311-2319.DOI:10.1016/j.cor.2008.09.010.
[5] MA Zujun,WU Yao,DAI Ying.A combined order selection and time-dependent vehicle routing problem with time windows for perishable product delivery[J].Computers&Industrial Engineering,2017,114:101-113.DOI:10.1016/j.cie.2017.10.010.
[6] OSVALD A,STIRN L Z.A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food[J].Journal of Food Engineering,2008,85(2):285-295.DOI:10.1016/j.jfoodeng.2007.07.008.
[7]邵举平,曹倩,沈敏燕,等.生鲜农产品配送中带时间窗的VRP模型与算法[J].工业工程与管理,2015(1):122-127.
[8] SONG B D,KO Y D.A vehicle routing problem of both refrigerated and general type vehicles for perishable food products delivery[J].Journal of Food Engineering,2016,169:61-71.DOI:10.1016/j.jfoodeng.2015.08.027.
[9]杨晓芳,姚宇,付强.基于新鲜度的冷链物流配送多目标优化模型[J].计算机应用研究,2016,33(4):1050-1053.DOI:10.3969./j.issn.1001-3695.2016.04.019.
[10]吴忠和,陈宏,赵千,等.时间约束下鲜活农产品供应链应急协调契约[J].系统管理学报,2014,23(1):49-56.
[11] BARKAOUI M,BERGER J,BOUKHTOUTA A.Customer satisfaction in dynamic vehicle routing problem with time windows[J].Applied Soft Computing,2015,35:423-432.DOI:10.1016/j.asoc.2015.06.035.
[12] SCHYNS M.An ant colony system for responsive dynamic vehicle routing[J].European Journal of Operational Research,2015,245(3):704-718.DOI:10.1016/j.ejor.2015.04.009.
[13]陈玉光,陈志祥.基于准时送货和最小耗油的配送车辆路径问题研究[J].中国管理科学,2015,23(s1):156-164.
[14]周辉仁,唐万生,王海龙.基于差分进化算法的多旅行商问题优化[J].系统工程理论与实践,2010,30(8):1471-1476.
[15] ZHANG Jingqiao,SANDERSON A C.JADE:adaptive differential evolution with optional external archive[J].IEEE Transactions on Evolutionary Computation,2009,13(5):945-958.